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Record W2130005887 · doi:10.1037/a0028494

Assessing the influence of letter position in reading normal and transposed texts using a letter detection task.

2012· article· en· W2130005887 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2012
Typearticle
Languageen
FieldComputer Science
TopicText Readability and Simplification
Canadian institutionsUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReading (process)Task (project management)Position (finance)Computer scienceNatural language processingPsychologyArtificial intelligenceSpeech recognitionAudiologyLinguisticsCognitive psychologyMedicinePhilosophyEngineering

Abstract

fetched live from OpenAlex

During word recognition, some letters appear to play a more important role than others. Although some studies have suggested that the first and last letters of a word have a privileged status, there is no consensus with regards to the importance of the different letter positions when reading connected text. In the current experiments, we used a simple letter search task to examine the impact of letter position on word identification in connected text using a classic paper and pencil procedure (Experiment 1) and an eye movement monitoring procedure (Experiment 2). In Experiments 3 and 4, a condition with transposed letters was included. Our results show that the first letter of a word is detected more easily than the other letters, and transposing letters in a word revealed the importance of the final letter. It is concluded that both the initial and final letters play a special role in word identification during reading but that the underlying processes might differ.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.317
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it